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In my opinion, douple-loop learning and connectivism complement and enhance each other.

Connectivism focuses on making connections (at external, conceptual, and neural levels)

On the other hand, double-loop learning aims at detecting and correcting errors by changing the values, strategies, and assumptions of the theory-in-use according to the new setting. Double-loop learning, however, does not recognize the power of connections/networks that help us operate in dynamic and uncertain environments, characterized by knowledge overload and fast-paced change.

Principles of connectivism Learning and knowledge rests in diversity of opinions. Learning is a process of connecting specialized nodes or information sources. Learning may reside in non-human appliances. Capacity to know more is more critical than what is currently known Nurturing and maintaining connections is needed to facilitate continual learning. Ability to see connections between fields, ideas, and concepts is a core skill. Currency (accurate, up-to-date knowledge) is the intent of all connectivist learning activities. Decision-making is itself a learning process. Choosing what to learn and the meaning of incoming information is seen through the lens of a shifting reality. While there is a right answer now, it may be wrong tomorrow due to alterations in the information climate affecting the decision.[3]